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dc.contributor.authorCao, Biao
dc.contributor.authorGastellu-Etchegorry, Jean-Philippe
dc.contributor.authorDu, Yongming
dc.contributor.authorLi, Hua
dc.contributor.authorBian, Zunjian
dc.contributor.authorHu, Tian
dc.contributor.authorFan, Wenjie
dc.contributor.authorXiao, Qing
dc.contributor.authorLiu, Qinhuo
dc.date.accessioned2020-09-09T22:55:50Z
dc.date.available2020-09-09T22:55:50Z
dc.date.issued2019
dc.identifier.issn0196-2892
dc.identifier.doi10.1109/TGRS.2019.2899600
dc.identifier.urihttp://hdl.handle.net/10072/397253
dc.description.abstractMany physical models have been proposed to simulate the directional anisotropy in the thermal infrared (TIR) region over vegetation canopies to produce angular corrected directional brightness temperature or land surface temperature. However, too many input parameters obstruct their operational use. Semiempirical kernel-driven models are designed to be a tradeoff between physical accuracy and operationality. Recently, four kernel-driven models have been proposed: the first two are direct extensions of kernel models in the visible- and near-infrared region and the last two were directly designed for the TIR region. In this paper, 153 continuous and 153 discrete canopies with varying structures and temperature distributions were considered in order to evaluate their accuracies against two physical models (4SAIL and DART). Their error distribution, scatterplots, and directional anisotropy patterns are compared. LSF-Li model, followed by Ross-Li, Vinnikov, and RL model, gave the best fitting results for all the scenes. The R 2 of all four kernel models can reach up to 0.82 for discrete scenes; however, the kernel-driven models underestimate the hotspot effect from continuous scenes; therefore, further improvements are necessary for operational use with future TIR satellite missions.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartofpagefrom5456
dc.relation.ispartofpageto5475
dc.relation.ispartofissue8
dc.relation.ispartofjournalIEEE Transactions on Geoscience and Remote Sensing
dc.relation.ispartofvolume57
dc.subject.fieldofresearchGeophysics
dc.subject.fieldofresearchGeomatic engineering
dc.subject.fieldofresearchcode3706
dc.subject.fieldofresearchcode4013
dc.subject.keywordsScience & Technology
dc.subject.keywordsPhysical Sciences
dc.subject.keywordsTechnology
dc.subject.keywordsGeochemistry & Geophysics
dc.subject.keywordsEngineering, Electrical & Electronic
dc.titleEvaluation of Four Kernel-Driven Models in the Thermal Infrared Band
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationCao, B; Gastellu-Etchegorry, J-P; Du, Y; Li, H; Bian, Z; Hu, T; Fan, W; Xiao, Q; Liu, Q, Evaluation of Four Kernel-Driven Models in the Thermal Infrared Band, IEEE Transactions on Geoscience and Remote Sensing, 2019, 57 (8), pp. 5456-5475
dc.date.updated2020-09-09T22:54:45Z
gro.hasfulltextNo Full Text
gro.griffith.authorHu, Tian


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